Motivation: Improvement of breast MRI images quality and better protocols, such as less noise, motion artifacts, better lesion characterization and less time, are still required in clinic. Goal(s): To investigate the potential benefit of deep learning reconstruction in T2 weighted and diffusion weighted images. Approach: 70 patients were performed T2 weighted, diffusion weighted images and AIR Deep Learning technology was used to do the reconstruction. Results: The image quality and visualization evaluation of deep learning (DL) reconstructed T2WI were significantly improved then T2WI, while DL-DWI didn't show advantage in compare with DWI and MUSE-DWI. Impact: This evaluation can be useful for reasonable T2WI and DWI breast imaging protocol picking based on deep learning methods, which may reducethepatients' uncomfortable or help better lesion characterization.
Yang et al. (2025) studied this question.